{"podcast":{"title":"Machine Learning Street Talk (MLST)","slug":"machine-learning-street-talk","podcast_index_feed_id":781643,"rss_url":"https://anchor.fm/s/1e4a0eac/podcast/rss","website_url":"https://podcasters.spotify.com/pod/show/machinelearningstreettalk","image_url":"https://d3t3ozftmdmh3i.cloudfront.net/staging/podcast_uploaded_nologo/4981699/4981699-1757416025703-f026fa81b6d04.jpg","author":"Machine Learning Street Talk (MLST)","episode_count":250,"summary":"Welcome! We engage in fascinating discussions with pre-eminent figures in the AI field. Our flagship show covers current affairs in AI, cognitive science, neuroscience and philosophy of mind with in-depth analysis. Our approach is unrivalled in terms of scope and rigour – we believe in intellectual diversity in AI, and we touch on all of the main ideas in the field with the hype surgically removed. MLST is run by Tim Scarfe, Ph.D (https://www.linkedin.com/in/ecsquizor/) and features regular appearances from MIT Doctor of Philosophy Keith Duggar (https://www.linkedin.com/in/dr-keith-duggar/).","last_synced_at":null,"page_url":"https://stenobird.com/podcast/machine-learning-street-talk"},"episode":{"title":"Jonas Hübotter (ETH) - Test Time Inference","slug":"jonas-h-botter-eth-test-time-inference","published_at":"2024-12-01T12:25:00+00:00","page_url":"https://stenobird.com/podcast/machine-learning-street-talk/jonas-h-botter-eth-test-time-inference","show_page_url":"https://stenobird.com/podcast/machine-learning-street-talk","url":"https://podcasters.spotify.com/pod/show/machinelearningstreettalk/episodes/Jonas-Hbotter-ETH---Test-Time-Inference-e2rnle4","audio_url":"https://anchor.fm/s/1e4a0eac/podcast/play/95196036/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2024-11-1%2Fc5b25fea-927b-5deb-5e11-619380dee886.mp3","summary":"Jonas Hübotter, PhD student at ETH Zurich's Institute for Machine Learning, discusses his groundbreaking research on test-time computation and local learning. He demonstrates how smaller models can outperform larger ones by 30x through strategic test-time computation and introduces a novel paradigm combining inductive and transductive learning approaches. Using Bayesian linear regression as a surrogate model for uncertainty estimation, Jonas explains how models can efficiently adapt to specific tasks without massive pre-training. He draws an analogy to Google Earth's variable resolution system to illustrate dynamic resource allocation based on task complexity. The conversation explores the future of AI architecture, envisioning systems that continuously learn and adapt beyond current monolithic models. Jonas concludes by proposing hybrid deployment strategies combining local and cloud computation, suggesting a future where compute resources are allocated based on task complexity rather than fixed model size. This research represents a significant shift in machine learning, prioritizing intelligent resource allocation and adaptive learning over traditional scaling approaches. SPONSOR MESSAGES: CentML offers competitive pricing for GenAI model deployment, with flexible options to suit a wide range of models, from small to large-scale deployments. https://centml.ai/pricing/ Tufa AI Labs is a brand new research lab in Zurich started by Benjamin Crouzier focussed on ARC and AGI, they just acquired MindsAI - the current winners of the ARC challenge. Are you interested in working on ARC, or getting involved in their events? Goto https://tufalabs.ai/ Transcription, references and show notes PDF download: https://www.dropbox.com/scl/fi/cxg80p388snwt6qbp4m52/JonasFinal.pdf?rlkey…","meta_description":"Jonas Hübotter, PhD student at ETH Zurich's Institute for Machine Learning, discusses his groundbreaking research on test-time computation and local learn…","key_points":[],"chapters":[],"topics":[],"duration_seconds":6356,"processing_state":"processed","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/machine-learning-street-talk/episodes/jonas-h-botter-eth-test-time-inference/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/machine-learning-street-talk/jonas-h-botter-eth-test-time-inference.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}